Scholia and scientometrics with Wikidata

Scholia is a tool to handle scientific bibliographic information in Wikidata. The Scholia Web service creates on-the-fly scholarly profiles for researchers, organizations, journals, publishers, individual scholarly works, and for research topics. To collect the data, it queries the SPARQL-based Wikidata Query Service. Among several display formats available in Scholia are lists of publications for individual researchers and organizations, publications per year, employment timelines, as well as co-author networks and citation graphs. The Python package implementing the Web service is also able to format Wikidata bibliographic entries for use in LaTeX/BIBTeX.Comment: 16 pages, 5 figures, Scientometrics 201

Take it personally - A Python library for data enrichment for infometrical applications

Like every other social sphere, science is influenced by individual characteristics of researchers. However, for investigations on scientific networks, only little data about the social background of researchers, e.g. social origin, gender, affiliation etc., is available. This paper introduces ”Take it personally - TIP”, a conceptual model and library currently under development, which aims to support the semantic enrichment of publication databases with semantically related background information which resides elsewhere in the (semantic) web, such as Wikidata. The supplementary information enriches the original information in the publication databases and thus facilitates the creation of complex scientific knowledge graphs. Such enrichment helps to improve the scientometric analysis of scientific publications as they can also take social backgrounds of researchers into account and to understand social structure in research communities

Bravo MaRDI: A Wikibase Powered Knowledge Graph on Mathematics

Mathematical world knowledge is a fundamental component of Wikidata. However, to date, no expertly curated knowledge graph has focused specifically on contemporary mathematics. Addressing this gap, the Mathematical Research Data Initiative (MaRDI) has developed a comprehensive knowledge graph that links multimodal research data in mathematics. This encompasses traditional research data items like datasets, software, and publications and includes semantically advanced objects such as mathematical formulas and hypotheses. This paper details the abilities of the MaRDI knowledge graph, which is based on Wikibase, leading up to its inaugural public release, codenamed Bravo, available on https://portal.mardi4nfdi.de.Comment: Accepted at Wikidata'23: Wikidata workshop at ISWC 202

Creating Structured Linked Data to Generate Scholarly Profiles: A Pilot Project using Wikidata and Scholia

INTRODUCTION Wikidata, a knowledge base for structured linked data, provides an open platform for curating scholarly communication data. Because all elements in a Wikidata entry are linked to defining elements and metadata, other web systems can harvest and display the data in meaningful ways. Thus, Wikidata has the capacity to serve as the data source for faculty profiles. Scholia is an example of how third-party tools can leverage the power of Wikidata to provide faculty profiles and bibliographic, data-driven visualizations. DESCRIPTION OF PROGRAM In this article, we share our methods for contributing to Wikidata and displaying the data with Scholia. We deployed these methods as part of a pilot project in which we contributed data about a small but unique school on the Indiana University-Purdue University Indianapolis (IUPUI) campus, the IU Lilly Family School of Philanthropy. NEXT STEPS Following the completion of our pilot project, we aim to find additional methods for contributing large data collections to Wikidata. Specifically, we seek to contribute scholarly communication data that the library already maintains in other systems. We are also facilitating Wikidata edit-a-thons to increase the library’s familiarity with the knowledge base and our capacity to contribute to the site

Wikidata and Libraries: Facilitating Open Knowledge

Book chapter preprint. Chapter published (2018) in "Leveraging Wikipedia: Connecting Communities of Knowledge" (pp. 143-158). Chicago, IL: ALA Editions.Libraries and archives are increasingly embracing the value of contributing information to open knowledge projects. Users come to Wikipedia—one of the best-known open knowledge projects—to learn about a specific topic or for quick fact checking. Even more serious researchers use it as a starting point for finding links to external resources related to their topic of interest. Wikipedia is just one of the many projects under the umbrella of the Wikimedia Foundation, a nonprofit charitable organization. Wikidata, for its part, is a sister project to Wikipedia. It stores structured data that is then fed back to the other Wiki projects, including Wikipedia, thus providing users with the most up-to-date information. This chapter focuses on Wikidata and its potential uses for libraries. We hope to inspire information professionals (librarians, archivists, library practitioners) to take the next step and start a conversation with their institutions and colleagues to free their data by contributing it to an open knowledge base like Wikidata

Robustifying Scholia: paving the way for knowledge discovery and research assessment through Wikidata

Knowledge workers like researchers, students, journalists, research evaluators or funders need tools to explore what is known, how it was discovered, who made which contributions, and where the scholarly record has gaps. Existing tools and services of this kind are not available as Linked Open Data, but Wikidata is. It has the technology, active contributor base, and content to build a large-scale knowledge graph for scholarship, also known as WikiCite. Scholia visualizes this graph in an exploratory interface with profiles and links to the literature. However, it is just a working prototype. This project aims to "robustify Scholia" with back-end development and testing based on pilot corpora. The main objective at this stage is to attain stability in challenging cases such as server throttling and handling of large or incomplete datasets. Further goals include integrating Scholia with data curation and manuscript writing workflows, serving more languages, generating usage stats, and documentation

ORCID for Wikidata. Data enrichment for scientometric applications

Due to its numerous bibliometric entries of scholarly articles and connected information Wikidata can serve as an open and rich source for deep scientometrical analyses. However, there are currently certain limitations: While 31.5% of all Wikidata entries represent scientific articles, only 8.9% are entries describing a person and the number of entries researcher is accordingly even lower. Another issue is the frequent absence of established relations between the scholarly article item and the author item although the author is already listed in Wikidata. To fill this gap and to improve the content of Wikidata in general, we established a workflow for matching authors and scholarly publications by integrating data from the ORCID (Open Researcher and Contributor ID) database. By this approach we were able to extend Wikidata by more than 12k author-publication relations and the method can be transferred to other enrichments based on ORCID data. This is extension is beneficial for Wikidata users performing bibliometrical analyses or using such metadata for other purposes

Riuso, interoperabilità, influenza: la cooperazione virtuosa tra i progetti SHARE e Wikidata

In the era of fragmentation of information, the integration and cooperation between different projects is needed to the speading of knowledge. The present work illustrates the processes to identify entities in the linked data projects of the "SHARE" family as well as the valuable contribution that Wikidata, the open knowledge base of the Wikimedia family, can give to such initiatives. In this context, the success indicators of the project, such as reuse, interoperability and influence, are observed to evaluate this cooperation and propose other possible forms of enrichment

LIS Journals\u27 Lack of Participation in Wikidata Item Creation

There are many items in Wikidata representing scholarly articles. However, these items have been created mostly by volunteer Wikidata editors and not systematically by journal publishers or editors, which can lead to gaps and inconsistencies in the datasets. This article presents findings from a survey investigating practices of library and information studies (LIS) journals in Wikidata item creation. Believing that a significant number of LIS journal editors would be aware of Wikidata and some would be creating Wikidata items for their publications, the authors sent a survey asking 138 English-language LIS journal editors if they created Wikidata items for materials published in their journal and follow-up questions. With a response rate of 41 percent, respondents overwhelmingly indicated that they did not create Wikidata items for materials published in their journal and were completely unaware of or only somewhat familiar with Wikidata. Respondents indicated that more familiarity with Wikidata and its benefits for scholarly journals as well as institutional support for the creation of Wikidata items could lead to greater participation; however, a campaign of education about Wikidata, documentation of benefits, and support for creation would be a necessary first step. The article presents and discusses the results of the survey, but the conclusions that can be drawn are minimal; therefore, the authors also discuss the benefits of creating Wikidata items for LIS journals as a first step in this educational campaign for editors and publishers